1. Field
The present disclosure relates to a system and a method for automated image quality based diagnosis of a document printing system. In particular, the present disclosure provides a hybrid approach that uses customer documents where possible and augments the customer documents with test patterns when necessary.
2. Description of Related Art
Diagnosis of image quality (IQ) problems is a difficult task. A number of document printing systems are able to send machine state and usage information back to the manufacturer or a service center. This information can be analyzed for diagnostic and prognostic purposes by field service personnel as well as product engineers. However, this information is usually not sufficient for diagnosing image quality problems.
Customer prints and/or special test patterns have been used to analyze image quality problems manually. For example, a customer or a service personnel may visually analyze the customer print and then provide inputs to the machine diagnoser. When visually examining the customer prints, there are some difficulties associated with identifying optimal test-patterns because a human observer tends to view image content on a qualitative basis rather than a quantitative basis. For example, the customer may notice a color shift on the sky blue color, but without further measurement or analysis, it may not be clear whether the color shift is on a 20% blue or a 12% blue. Thus the customer inputs may not be very accurate in specifying an optimal test-pattern for further analyses. In another instance, for example, the customer or service personnel may notice a banding issue on a light orange background. The customer or service personnel, however, may not be able to identify the frequency or frequencies of the banding and/or the fractions of colorants that make the light orange background, where the banding issue was observed. Further, analyzing the customer prints and/or special test patterns manually is a reactive approach, in that images are analyzed only after the customer notices image quality defects or artifacts.
When a field service engineer arrives at a customer site to service an image quality related problem, he/she typically has no a priori insight into the reason for the problem. The machine data available from the machine provides very little image quality related information. Moreover, the actual process of image quality diagnostics by a field engineer is a time consuming and a wasteful process. Since there is usually no a priori information available regarding the image quality trends of a machine, it may be necessary to print a number of test patterns. This can be time consuming, costly and not very environmentally conscious or “green” (e.g., waste of paper, scanning, analyses). Existing methods (See e.g., U.S. Patent Publication Nos. 2006/0110009 and 2008/0013848; U.S. patent Publication Ser. No. 12/018,540 filed on Jan. 23, 2008 by Wencheng Wu et al. entitled “SYSTEM AND METHODS FOR DETECTING IMAGE QUALITY DEFECTS”) focus on reducing some of the “waste” by sensing and analyzing customer documents. Although these methods have shown some successes, there are fundamental limitations and technology difficulties that limit their current performance. One limitation, for example, is that the customer may not print a certain colorant combination at certain spatial locations which may be critical for diagnosis and/or characterization. Another example is the strict requirement of accuracy on image registration including global and local distortion. Yet another example is that it is rare to have a large enough area of desired constant color, in order to generate accurate image quality information for diagnostics in the customer documents.
It is thus desirable to accumulate detected defects over many prints and then interpolate/extrapolate them for the purpose of diagnostics. With interpolation, it is difficult to detect certain defects accurately such as those with high spatial frequency. Thus, due to these challenges faced by technologies that sense and analyze only customer documents, there is a need to have auxiliary use of test patterns/prints. Also, while numerous proposals and some implementations of in situ monitoring have been made, the present disclosure differs in using customer documents where possible and augmenting with test patterns when necessary.